Projects
Computer vision, scientific visualization, and applied data science.
EvacSim: Evacuation Simulation using MAS
Real-time evacuation tool with 9 autonomous agents — 8 drones and 1 vehicle — using Unity AI NavMesh and React frontend with WebSocket streaming.
Algae Identification Towards Automated Classification
Applied ResNet and U-Net to identify 12 algae species for the City of Bloomington, improving Lake Monroe water quality monitoring.
Bridging the Gender Gap in Heart Attack
Ensemble models and feature importance for gender-related risk differences.
When Asteroids Strike: Deep Water Collisions
Visualized asteroid collision scenarios with ParaView and spatial data.
Natural Statistics of Infant Visual Experience
Image statistics from infant head cameras across US & India.
Experience
Research Data Scientist
- Analyzing 500,000+ egocentric head-camera images/videos from infants aged 4–30 months to investigate how visual input changes by age and impacts early visual development.
- Developing computer vision pipelines using feature-congestion scores, image segmentation models, and semantic measures to quantify visual complexity in infant environments.
- Collaborating with cognitive development researchers and AI engineers to translate CV findings into actionable insights, bridging AI/ML with developmental psychology.
Associate Instructor
- Instructed over 30 students through hands-on lab sessions covering Python, Arduino, HTML, CSS, Java, and EarSketch, fostering foundational problem-solving skills.
- Conducted daily office hours to assist students in overcoming coding challenges and building strong computational thinking abilities.
Linguistic Data Annotator – Apple Siri Project
- Evaluated and annotated 370+ language model training samples daily, developing understanding of how training data quality impacts AI system behavior and output alignment.
- Designed culturally nuanced Korean dialogues to improve AI conversational quality, contributing to alignment between model outputs and human communication norms.
Education
Indiana University Bloomington
MS in Data Science – Applied Data Science
GPA: 3.8 / 4.0
Relevant Courses: Machine Learning, Computer Vision, Natural Language Processing, Applied Databases, Statistics, Scientific Visualization, Information Visualization, Data Mining, Social Media Mining, Independent Study
Konkuk University
Bachelor of Business Administration
GPA: 3.72 / 4.5
Relevant Courses: Environmental Analysis, Marketing Research, Advertising
Technical Skills
About Me
Research Data Scientist at the Cognitive Development Lab, Indiana University. MS Data Science graduate specializing in Machine Learning and Computer Vision at the Luddy School of Informatics, Computing, and Engineering.
My path started with Business Administration. A marketing internship in South Korea sparked my curiosity in AI and data-driven decisions, leading me to pursue a Master's in Data Science — focusing on Machine Learning, Computer Vision, NLP, and Scientific Visualization. I'm passionate about building AI systems that bridge research and real-world impact.
Get In Touch
Always open to connecting about data science, research, and AI.